The Long Game

Kitchen Side: The Hidden Drivers of AI Search

Episode Summary

A candid look at why self-reported attribution beats clickstream data in AI search, and how visibility works more like a brand mirror than a channel.

Episode Notes

In this Kitchen Side episode, Alex Birkett, Allie Decker, and David Ly Khim unpack how brands should actually measure success in AI search, and why traditional attribution models are breaking down as buyer behavior shifts from search links to AI assistants and workflows.

They discuss why self-reported attribution is becoming the most reliable signal available, the different tiers of AI visibility from simple citations to category-level consensus, and why AI visibility functions more like a brand recall survey than a channel you can optimize in isolation. The conversation also covers the idea of a “post-channel marketer” who coordinates across product, customer education, and PR, and why chasing visibility tactics with no underlying business purpose rarely pays off.

Key Takeaways

• Self-reported attribution is more reliable than clickstream data for AI search because most AI-driven visits never result in a tracked click.
• AI visibility behaves more like a brand recall survey than a channel, reflecting how a brand compares to competitors rather than something to optimize in isolation.
• Picking up a citation on a narrow, low-competition prompt is easy, but shifting broader category-level consensus, like being named among the best CRMs, is far harder and requires changing an entire conversation.
• Correcting outdated third-party pricing information moved AI search outputs within about a month in one client engagement, though this was a sentiment fix rather than a visibility gain.
• Some AI answers now include negative or qualifying recommendations, meaning a mention doesn't always translate into a positive outcome for a brand.
• Different AI tools serve different roles, with ChatGPT and AI Overviews functioning as quick answer engines while agentic tools like Claude Code perform deeper multi-step research, and visibility strategies should account for that difference.
• Whether a company should publish a markdown version of its site for easier AI retrieval depends on its audience, mattering more for technical, developer-facing products than for typical B2B SaaS buyers.
• Sustainable AI search performance comes from investing in product experience, customer education, and reviews, since genuine third-party validation is difficult to fake once a brand has earned it.
• Marketing teams need a “post-channel” role that coordinates across product, customer success, and PR to influence sentiment and visibility, rather than treating this as an SEO-only or PR-only problem.
• Tactics pursued only to move an AI visibility score, with no underlying business purpose, are usually not worth the effort unless they're addressing existing negative sentiment.

Show Links

• Connect with David Khim on LinkedIn and Twitter
• Connect with Alex Birkett on LinkedIn and Twitter
• Connect with Allie Decker on LinkedIn and Twitter
• Connect with Omniscient Digital on LinkedIn or Twitter

What is Kitchen Side?

One big benefit of running an agency or working at one is you get to see the "kitchen side" of many different businesses; their revenue, their operations, their automations, and their culture.

You understand how things look from the inside and how that differs from the outside.

You understand how the sausage is made.

As an agency ourselves, we're working both on growing our clients' businesses as well as our own. This podcast is one project, but we also blog, make videos, do sales, and have quite a robust portfolio of automations and hacks to run our business.

We want to take you behind the curtain, to the kitchen side of our business, to witness our brainstorms, discussions, and internal dialogues behind the public works that we ship.

Past guests on The Long Game podcast include: Morgan Brown (Shopify), Ryan Law (Animalz), Dan Shure (Evolving SEO), Kaleigh Moore (freelancer), Eric Siu (Clickflow), Peep Laja (CXL), Chelsea Castle (Chili Piper), Tracey Wallace (Klaviyo), Tim Soulo (Ahrefs), Ryan McReady (Reforge), and many more.

Some interviews you might enjoy and learn from:

• Actionable Tips and Secrets to SEO Strategy with Dan Shure (Evolving SEO)
• Building Competitive Marketing Content with Sam Chapman (Aprimo)
• How to Build the Right Data Workflow with Blake Burch (Shipyard)
• Data-Driven Thought Leadership with Alicia Johnston (Sprout Social)
• Purpose-Driven Leadership & Building a Content Team with Ty Magnin (UiPath)

Also, check out our Kitchen Side series where we take you behind the scenes to see how the sausage is made at our agency:

• Blue Ocean vs Red Ocean SEO
• Should You Hire Writers or Subject Matter Experts?
• How Do Growth and Content Overlap?

Connect with Omniscient Digital on social:

Twitter: @beomniscient

LinkedIn: Be Omniscient

Listen to more episodes of The Long Game podcast here: https://beomniscient.com/podcast/

Episode Transcription

[00:00] – Intro and episode overview: measuring success in AI search
[04:41] – Why "is it working" has become the bigger question than "how do we show up"
[05:34] – The case for self-reported attribution over clickstream data
[06:28] – AI visibility as a mirror or brand recall survey
[07:25] – Analyzing lead data to see how often AI referrals go untracked
[11:44] – How quickly results can show up in AI search
[12:42] – A study on "poisoning" AI answers with just 13 words
[14:40] – Case study: correcting third-party pricing information shifted AI outputs within a month
[16:34] – The ladder of AI search results, from easy citations to hard-won category consensus
[20:45] – Negative AI recommendations and exclusion from the consideration set
[29:32] – Why different AI tools, like ChatGPT vs. Claude Code, need different visibility strategies
[35:49] – Probability engineering and the "post-channel marketer" concept
[44:25] – Should you do something only to move an AI visibility score?